Instructions to use hf-internal-testing/tiny-ShapEPipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-ShapEPipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-ShapEPipeline", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 645a022f243b7f8deb282633eadd642c26a75836bebb2c357ff6343efdf16591
- Size of remote file:
- 127 kB
- SHA256:
- 666286f04533ecbad1fe972f1cee2c32ab62aba4ec74b51da1bdf5d848d73664
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